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daily_stock_analysis hands-on: a failed fetch became '0' market volume

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daily_stock_analysis hands-on: a failed fetch became '0' market volume

3 Key Points

  1. What happened

    Running ZhuLinsen's daily_stock_analysis locally with Ollama's qwen2.5:7b-instruct, the author found that --dry-run still triggered the market-review LLM call, and when all six stats sources failed, the review asserted trading volume was 0.

  2. Why it matters

    A stock tool that cannot tell missing data from a real zero can hand readers confident-looking analysis built on nothing, and the same run left two of three stocks on placeholder text.

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Context & Analysis

The tool itself is real: the offline unit tests passed 8,476 cases in about 12 minutes, and data fetching routed correctly per market, pulling actual recent closes such as 600519's 1453.00/1444.99/1439.00 yuan over three sessions. The problems surfaced only when the free, local path was actually exercised.

The market review is where the design gap shows. Six data sources failed in sequence -- a JSON parse error, two 30-second Akshare timeouts, and four providers with no matching data -- yet the prompt handed the model only the number 0, with no context that the fetch had failed. Individual stock dashboards, by contrast, carry an explicit data-limitation field listing missing volume, chip-structure and quote data, so the omission appears specific to the market-review path.

Output stability is the other finding. On the local 7B model, schema validation errors recurred and fallback filling kept the pipeline from stopping, which is why the run was counted as a success despite placeholder content. The later stall of the second market review, while Ollama stayed responsive to a direct curl, is recorded as reproducible but not diagnosed in the source code.

FAQ
Did the --dry-run option really skip all LLM calls?
No. Individual stock AI analysis was skipped, but the market-wide review still ran through Ollama and produced a 984-character report file.
How did the local 7B model perform on the full run?
The pipeline reported 3 successes in 58.13 seconds, but JSON schema validation failed repeatedly, and two of the three stocks kept placeholder text like 'analysis complete' and 'to be filled' for the stop-loss level.
What were the final scores for the three stocks?
Toyota (7203.T), Guizhou Moutai (600519) and Apple (AAPL) all ended with the same 'score 50, hold, range-bound' result.
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